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Inter-channel mis-synchronisation can be a limiting factor to the time resolution of high performance timing detectors with multiple readout channels and independent electronics units. In these systems, time calibration methods employed must be able to efficiently correct for minimal mis-synchronisation between channels and achieve the best detector performance. We present an iterative time calibration method based on Markov Chains, suitable for detector systems with multiple readout channels. Starting from correlated hit pairs alone, and without requiring an external reference time measurement, the method solves for fixed per-channel offsets, with precision limited only by the intrinsic single-channel resolution. A mathematical proof that the method is able to find the correct time offsets to be assigned to each detector channel in order to achieve inter-channel synchronisation is given, and it is shown that the number of iterations to reach convergence within the desired precision is controllable with a single parameter. Numerical studies are used to confirm unbiased recovery of true offsets. Finally, the application of the calibration method to the Super Fine-Grained Detector (SuperFGD) and the Time of Flight (TOF) detector at the upgraded T2K near detector (ND280) shows good improvement in overall timing resolution, demonstrating the effectiveness in a real-world scenario and scalability.

The magnetised near detector ND280 of the long-baseline neutrino experiment T2K has been upgraded to improve its detection performance and, consequently, enhance our understanding of neutrino-nucleus interactions, reducing the systematic uncertainties in measurements of the neutrino oscillation parameters. A key component of the upgrade is a novel segmented plastic scintillator detector, called the Super Fine-Grained Detector (SuperFGD), made of approximately 2 million optically isolated 1 cm\\(^3\\) cubes read out by three orthogonal wavelength-shifting (WLS) fibres. Scintillation photons are detected by 55,888 Hamamatsu Multi-Pixel Photon Counters (MPPCs). The SuperFGD provides 3D images of neutrino interactions by tracking the final-state charged particles produced isotropically, including protons down to a threshold of around 330 MeV/\\(c\\). The high light yield of SuperFGD greatly improves particle identification and the sub-nanosecond time resolution provides an excellent identification of Michel electrons. The SuperFGD is also able to detect neutrons from neutrino interactions and, for the first time in a neutrino experiment, to reconstruct their kinetic energy using a fine detector segmentation and by measuring the time-of-flight with sub-nanosecond precision. In this article the details of the detector design, construction and performance are described. The detector was installed in ND280 and successfully commissioned with cosmic data in 2023 and, later, with the T2K neutrino beam. The detector response has been characterised with the 2023 and 2024 data and the results are reported in this article.

Inter-channel mis-synchronisation can be a limiting factor to the time resolution of high performance timing detectors with multiple readout channels and independent electronics units. In these systems, time calibration methods employed must be able to efficiently correct for minimal mis-synchronisation between channels and achieve the best detector performance. We present an iterative time calibration method based on Markov Chains, suitable for detector systems with multiple readout channels. Starting from correlated hit pairs alone, and without requiring an external reference time measurement, the method solves for fixed per-channel offsets, with precision limited only by the intrinsic single-channel resolution. A mathematical proof that the method is able to find the correct time offsets to be assigned to each detector channel in order to achieve inter-channel synchronisation is given, and it is shown that the number of iterations to reach convergence within the desired precision is controllable with a single parameter. Numerical studies are used to confirm unbiased recovery of true offsets. Finally, the application of the calibration method to the Super Fine-Grained Detector (SuperFGD) and the Time of Flight (TOF) detector at the upgraded T2K near detector (ND280) shows good improvement in overall timing resolution, demonstrating the effectiveness in a real-world scenario and scalability.

This article presents a study of single \\(^+\\) production in neutrino neutral-current interactions (NC1\\(^+\\)) using the FGD1 hydrocarbon target of the ND280 detector of the T2K experiment. We report the largest sample of such events selected by any experiment, providing the first new data for this channel in over four decades and the first using a sub-GeV neutrino flux. The signal selection strategy and its performance are detailed together with validations of a robust cross section extraction methodology. The measured flux-averaged integrated cross-section is \\( = (6.07 1.22 ) 10^-41 \\,\\, cm^2/nucleon\\), 1.3~\\(~\\) above the NEUT v5.4.0 expectation.

Since its first observation in the 1970s, neutrino-induced neutral-current single positive pion production (NC1\\(^+\\)) has remained an elusive and poorly understood interaction channel. This process is a significant background in neutrino oscillation experiments and studying it further is critical for the physics program of next-generation accelerator-based neutrino oscillation experiments. In this Letter we present the first double-differential cross-section measurement of NC1\\(^+\\) interactions using data from the ND280 detector of the T2K experiment collected in \\(\\)-beam mode. The measured flux-averaged integrated cross-section is \\( = (6.07 1.22 ) 10^-41 \\,\\, cm^2/nucleon\\). We compare the results on a hydrocarbon target to the predictions of several neutrino interaction generators and final-state interaction models. While model predictions agree with the differential results, the data shows a weak preference for a cross-section normalization approximately 30\\% higher than predicted by most models studied in this Letter.

We report the first measurement of neutron capture multiplicity in neutrino-oxygen neutral-current quasi-elastic-like interactions at the gadolinium-loaded Super-Kamiokande detector using the T2K neutrino beam, which has a peak energy of about 0.6 GeV. A total of 30 neutral-current quasi-elastic-like event candidates were selected from T2K data corresponding to an exposure of \\(1.7610^20\\) protons on target. The \\(\\) ray signals resulting from neutron captures were identified using a neural network. The flux-averaged mean neutron capture multiplicity was measured to be$1.37\\pm0.33\\text{ (stat.)}$ $^{+0.17}_{-0.27}\\text{ (syst.)}\\(, which is compatible within \\)2.3\\,\\sigma$than predictions obtained using our nominal simulation. We discuss potential sources of systematic uncertainty in the prediction and demonstrate that a significant portion of this discrepancy arises from the modeling of hadron-nucleus interactions in the detector medium.

The magnetised near detector (ND280) of the T2K long-baseline neutrino oscillation experiment has been recently upgraded aiming to satisfy the requirement of reducing the systematic uncertainty from measuring the neutrinonucleus interaction cross section, which is the largest systematic uncertainty in the search for leptonic charge-parity symmetry violation. A key component of the upgrade is SuperFGD, a 3D segmented plastic scintillator detector made of approximately 2,000,000 optically-isolated 1 cm3 cubes. It will provide a 3D image of GeV neutrino interactions by combining tracking and stopping power measurements of final state particles with sub-nanosecond time resolution. The performance of SuperFGD is characterized by the precision of its response to charged particles as well as the systematic effects that might affect the physics measurements. Hence, a detailed Geant4 based optical simulation of the SuperFGD building block, i.e. a plastic scintillating cube read out by three wavelength shifting fibers, has been developed and validated with the different datasets collected in various beam tests. In this manuscript the description of the optical model as well as the comparison with data are reported.

With the climate rapidly changing, coniferous trees in North America face many threats, and both native and invasive insects are contributing to their decline and mortality. As insects, particularly bark beetles, successfully attack trees, the foliage of those trees undergoes a color shift from green to red to gray. Attacks from other insects, such as defoliators, can result in defoliation, crown thinning, and loss of needles. These changes may be detected by remote sensing instruments such as satellites and drones. Tree mortality may also come from multiple other variables, such as fire or drought, which then causes tree stress, making plants more susceptible to insect infestation.I analyzed an area with tree disturbance and mortality from three distinct types of insects in Montana, United States to study the detection of forest disturbance by insect outbreaks. This study aims to examine the patterns displayed across a section of forest at different spatial resolutions and scales. Field studies consisted of measuring variables such as diameter, health, and needle color on both trees inside eight-meter fixed-radius plots as well as individual trees not within plots. I analyzed and classified imagery from various sensors, including data from an unmanned aerial vehicle and multiple satellites. Pixels from these data sets are classified using two modeling techniques: maximum likelihood and random forest. This resulted in maps of different tree health classes and other land classes such as bare ground and herbaceous vegetation. I evaluated tree disturbance with classifications of finer spatial resolution pixels (subpixels), which were aggregated to the size of coarser spatial resolution pixels (superpixels) by calculating the percentage of unhealthy trees within, and then comparing them to the classification of the actual classified superpixels. By comparing classification results at different resolution levels, it is possible to extract what information was retained or lost at each step down in spatial resolution, and field measurements provided corroborating evidence of tree disturbance.Random forest models outperformed maximum likelihood models based on accuracy of withheld evaluation points, with overall accuracies ranging from 81.5% to 94.5%. Corroboration of individual trees from the field data was only easily feasible with UAV data, plausible with WorldView-3 data, and not possible with any imagery of 10-m spatial resolution or coarser. Total percent area affected of unhealthy trees was not consistent across resolutions, although coarser imagery tended to underestimate mortality or damage for most intensities of finer imagery disturbance when grouped into distinct disturbance bins but predict more mortality or disturbance across an entire landscape. This study will assist forest managers and natural resource scientists in understanding detection of insect-affected forests, in particular when insect outbreaks are more diffuse and not severe across the entire landscape, giving managers guidelines for where to invest time and resources. This research will also allow for general trends for areas with insect-specific mortality, allowing for potential future comparisons with other causes of tree mortality.